Business intelligence (BI) is of utmost importance to businesses. Business intelligence involves performing data analytics to answer questions of interest to the business. An example question may be “What is my sales number for this quarter for a certain region.” Another question may be “From available data, who are the customers who may likely be defecting to a competitor.” In performing data analytics-based business intelligence (DA-BI), it is necessary to gather data from a variety of sources, organize the data, analyze the data, and present the analytics result in a manner that makes sense to the user.
There are existing software applications for performing DA-BI currently. These applications permit the acquisition of data, the organization of stored data, the application of business rules to perform the analytics, and the presentation of the analytics result. In the past, such applications require the use of an expert system integrator company or highly skilled personnel in the IT department (often a luxury that only the largest companies can afford) since these tools require custom coding, custom configuration and heavy customization.
The explosion in the volume of data in the last few years means that the customer now has more data and more variety of data formats to work with. At the same time, customers are demanding more in-depth answers from the available data. This increase in data volume and data formats, as well as the increased need of customers, has created a need to update or change many existing business intelligence applications. However, due to the customized hard coding nature of existing BI-applications, many businesses have not been willing or simply do not have the money and/or time to commit to updating their existing BI system or purchasing a new BI system.
Furthermore, new technologies are now available for data storage, data acquisition, data analysis, and presentation. Big data or cloud computing (whether open-source or proprietary) are some examples of such technologies. Some of these technologies have not yet been widely adopted by the BI industry. Being new, the level of expertise required to make use of these technologies is fairly high since there are fewer people familiar with these technologies. This trend drives up the cost of implementing new BI systems or updating existing BI systems for customers, particularly if the customers desire to make use of the new technologies.
In view of the foregoing, there is a need for a new approach to create and/or update data analytics applications for customers.